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Automated machine learning : methods, systems, challenges / edited by Frank Hutter, Lars Kotthoff, and Joaquin Vanschoren

Contributor(s): Material type: TextTextPublication details: Switzerland : Springer, c2019Description: xiv, 219 pages : illustrations ; 24 cmISBN:
  • 9783030053178
Subject(s): LOC classification:
  • Q 325.5 .A98 2019
Contents:
Part I : AutoML methods -- 1. Hyperparameter optimization -- 2. Meta-learning -- 3. Neural architecture search -- Part II : AutoML systems -- 4. Auto-WEKA : automatic model selection and hyperparameter optimization in WEKA -- 5. Hyperopt-sklearn -- 6. Auto-sklearn : efficient and robust automated machine learning -- 7. Towards automatically-tuned deep neural networks -- 8. TPOT : A Tree-based pipeline optimization tool for automating machine learning -- 9. The Automatic statistician -- Part II : AutoML challenges -- 10. Analysis of the autoML challenge series 2015-2018
Summary: This open access book presents the first comprehensive overview of general methods in autmated machine learning (AutoML), collects descriptions of existing systems based on these methiods, and discusses the first series of international challenges of AutoML systems.
Item type: Books
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Includes bibliographical references.

Part I : AutoML methods -- 1. Hyperparameter optimization -- 2. Meta-learning -- 3. Neural architecture search -- Part II : AutoML systems -- 4. Auto-WEKA : automatic model selection and hyperparameter optimization in WEKA -- 5. Hyperopt-sklearn -- 6. Auto-sklearn : efficient and robust automated machine learning -- 7. Towards automatically-tuned deep neural networks -- 8. TPOT : A Tree-based pipeline optimization tool for automating machine learning -- 9. The Automatic statistician -- Part II : AutoML challenges -- 10. Analysis of the autoML challenge series 2015-2018

This open access book presents the first comprehensive overview of general methods in autmated machine learning (AutoML), collects descriptions of existing systems based on these methiods, and discusses the first series of international challenges of AutoML systems.

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